Director leading Cint’s enterprise AI transformation office driving measurable business value. Overseeing AI strategy and roadmap while managing high - impact teams and complex workflows.
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Generative AI Specialist – Humanities, English, Japanese
Posted 3 months ago
About the role
- Generative AI Specialist contributing to cutting-edge AI development, focusing on language and reasoning for large language models. Join a global contributor community at Innodata, a leading data engineering company.
Responsibilities
- Evaluation: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions.
- Annotation Labeling: Labeling elements of a piece of content rather than the content as a whole.
- Classification: Assigning predefined categories or labels to items.
- Content Quality: Evaluating the perceived quality and/or appropriateness of content
- Content Understanding: Generating labels to advance understanding of a concept, trend etc.
- Data Augmentation: Creation of additional training data for machine learning models by applying transformations to the original data.
- Grading: Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines.
- Identification Labeling: Labeling model outputs to identify if a piece of content is or isn't something.
- Preference Ranking: Ordering or ranking items based on a set of preferences or criteria.
- Prompt Generation: Creating prompts or questions that will be used to generate responses from a language model or other AI system.
- Relevance Evaluation: Projects that evaluate the relevance of content based on a relevancy scale.
- Response Generation: Generating responses to prompts or questions using a language model or other AI system.
- Response Rewrite: Rewriting existing text while preserving the original meaning.
- Response Summarization: Producing concise summaries of longer pieces of text or data.
- Similarity Evaluation: Projects where content is compared in order to drive a determination.
- Transcription: Converting spoken language or audio content into written text.
- Translation: Converting text or spoken language from one language to another.
- Data Collection: Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models.
Requirements
- A Bachelor’s degree or higher in a humanities specialization is required
- Advanced degrees are strongly preferred (Master’s or PhD)
- Professional or Expert level proficiency (C1/C2) in English and Japanese
Benefits
- Part-Time; up to 28 hours per week
- Remote work options
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